[Paper Review] Proceedings of the workshop: HERA and the LHC workshop series on the implications of HERA for LHC physics

H. Jung, A. De Roeck+267 more|arXiv (Cornell University)|Jan 1, 2009

Particle physics theoretical and experimental studies3 references35 citations

TL;DR

This workshop proceedings synthesizes insights from HERA and LHC physics, emphasizing how HERA's precision data on parton densities, jet dynamics, heavy quarks, and diffraction significantly reduce uncertainties in LHC predictions. By promoting shared PDF fitting, validated Monte Carlo tools like Rivet, and corrected experimental data, the work establishes a framework for cross-collaboration that enhances LHC physics reach through HERA-derived constraints and improved theoretical modeling.

ABSTRACT

2nd workshop on the implications of HERA for LHC physics. Working groups: Parton Density Functions Multi-jet final states and energy flows Heavy quarks (charm and beauty) Diffraction Cosmic Rays Monte Carlos and Tools

Motivation & Objective

• To identify and prioritize HERA measurements that most significantly impact LHC physics reach.
• To foster knowledge transfer between HERA and LHC communities to enhance theoretical and experimental tools.
• To improve the precision of parton distribution functions (PDFs) through combined H1 and ZEUS data analysis.
• To validate Monte Carlo event generators using detector-corrected data and promote reproducibility via Rivet.
• To establish a framework for future LHC physics by leveraging HERA’s precision in QCD dynamics, heavy flavors, and diffraction.

Proposed method

• Conducting joint global fits of H1 and ZEUS data to constrain parton distribution functions (PDFs), especially at low-x and in gluon distributions.
• Implementing advanced jet algorithms (e.g., SISCone, (anti)-kT) and defining jet quality measures for multi-jet and energy flow studies.
• Developing and applying kT factorization formalisms to extract unintegrated gluon distributions from HERA data.
• Using corrected, detector-effect-corrected data from HepData to validate Monte Carlo generators and ensure reproducibility.
• Integrating experimental analyses into the Rivet validation framework to guarantee exact, model-agnostic reproduction of results.
• Promoting the use of covariance matrices for correlated errors to preserve statistical integrity in future model validation.

Experimental results

Research questions

• RQ1 How do combined H1 and ZEUS HERA data improve the precision and reduce uncertainties in global PDF fits?
• RQ2 To what extent can HERA measurements of jet production and energy flow inform LHC jet physics and QCD dynamics?
• RQ3 How can unintegrated gluon distributions extracted from HERA data enhance predictions for LHC processes like vector boson or heavy quark production?
• RQ4 What role do corrected, detector-corrected data and covariance matrices play in validating Monte Carlo event generators for LHC simulations?
• RQ5 How can the Rivet framework ensure long-term reproducibility and model-agnostic validation of published LHC and HERA analyses?

Key findings

• The combination of H1 and ZEUS data significantly improves PDF precision, especially for gluon distributions at low-x, reducing uncertainties beyond individual experiment fits.
• Measuring the longitudinal structure function FL at HERA resolved long-standing discrepancies in NLO gluon distributions, validating theoretical predictions.
• The PDF4LHC initiative was launched as a direct outcome, standardizing PDF fitting procedures and promoting common analysis frameworks across the global PDF community.
• Jet algorithms such as SISCone and (anti)-kT were validated for infrared and collinear safety, with performance benchmarks established for LHC jet physics.
• Unintegrated gluon distributions were formalized as extractable from HERA data, enabling improved predictions for high-multiplicity and forward jet processes at the LHC.
• The integration of corrected data into HepData and the Rivet framework ensures long-term reproducibility and enables future validation of Monte Carlo generators, with LEP data serving as a successful precedent.